Sunday, November 1, 2009

The September/October 2009 issue of Child Development includes an article entitled, "Correlates and Consequences of Spanking and Verbal Punishment for Low-Income White, African American, and Mexican American Toddlers." The article was authored by Duke University's Lisa Berlin and a long list of co-authors from multiple institutions; the eight authors of the article were themselves representing an even larger set of investigators who formed the Early Head Start Research Consortium. The abstract of the article is available here. I would like to thank Jonathan Mueller for bringing the article to my attention and suggesting I comment upon it.

The Berlin et al. article is an example of a longitudinal/panel study, from which causal inference is potentially very good, but never complete (see earlier posting on this topic). Given the emotional reaction many people have to spanking and related issues, however, any article of this type is bound to receive great scrutiny.

The study drew a sample of 2,573 children and their primary caregivers (99% mothers) from 17 sites nationally. Families were assessed when the children were 1, 2, and 3 years of age, with key study variables including parental spanking and verbal punishment, and child fussiness (EASI II temperamental emotionality; age 1 only), aggression (CBCL), and mental development (Bayley scores). The latter two child outcomes were measured only at ages 2 and 3. The authors addressed causality issues in the Introduction, on pp. 1405-1406:

In keeping with transactional theories of child development... another question requiring further study concerns the direction of effects. In particular, to what extent do parental discipline strategies drive child outcomes, to what extent are these parenting strategies elicited by particular child behaviors, and to what extent are both causal mechanisms operative? ... As recommended by Gershoff and Bitensky, cross-lagged path models that simultaneously estimate effects from parental discipline strategies to child behaviors and vice versa are critical to disentangling such issues.

Some of the key statistically significant findings from the regression analyses were as follows:

Two of the criteria for causality -- presence of statistical association and time-ordering -- are clearly met for the above relationships. The third and final criterion is that all possible "third variables" (e.g., something that might cause both spanking and child aggression) are ruled out. No study can ever rule out all possible third variables, so a more realistic question is whether the investigators ruled out the most plausible contenders. Quoting from the Table 5 caption, Berlin et al report controlling for "Early Head Start program participation, maternal race/ethnicity, age, and education, maternal depression at age 1, family income and structure, and child sex." It also appears from Table 5 and Figure 1 that the significant path from age-1 spanking to age-2 child aggression was obtained while controlling for age-1 child fussiness (i.e., an age-1 fussiness to age-2 aggression path was also included in the model, and was significantly positive).

The above set of control variables seems fairly comprehensive, but observers can usually suggest more (some more plausible than others). A skeptic might note that the study design was not "genetically informed," in other words, not able to examine rigorously whether, for example, genetic tendencies toward irritability that may have been shared between mother and child may have contributed to the obtained relationships (a phenomenon known as passive gene-environment correlation). Controlling for child fussiness probably helps a little bit in overcoming this objection, although it would have been good to control for symptoms of other forms of maternal psychopathology besides depression.

It is important to add, however, that the authors appear to have gone to great pains to examine the possible strengths and weaknesses of their study, in order to present an honest appraisal of the findings. Specifically, they undertook a number of supplementary analyses to (potentially) qualify the scope of their conclusions, including tests for whether the basic results held up equally well across different racial/ethnic groups (i.e., moderation) and whether removing the most "severe" spankers affected the results. They also discussed what they perceived as limitations to their own study, such as the self-report measure of spanking not containing a specific definition of the act, and acknowledged that the results suggesting an effect of spanking were of "small," though significantly non-zero, magnitude.

Berlin et al. summarize their study as follows:

[The findings] support the conclusion that spanking during toddlerhood can have negative consequences for toddlers' cognitive as well as socioemotional functioning (p. 1417).

I find this conclusion appropriate. As noted, the authors' research design approaches causality about as well as is possible with a non-experimental study, and the use of "can" as a qualifier in the preceding quote conveys the necessary caution.

UPDATE (May 17, 2010): Robert Larzelere, a faculty member at Oklahoma State University whose interests include causal inference from longitudinal surveys, e-mailed me a few weeks ago that he and his colleagues had published some articles on spanking and alternative sources of discipline. Here's a link to his list of publications, from which interested readers can see the kinds of issues Dr. Larzelere has raised regarding causal inference and parental discipline.

Thursday, October 22, 2009

Nick Barrowman, who operates the blog "Log base 2," examines a study reported on MSNBC.com showing a strong correlation (.72) between states' teenage birthrates and conservative religiosity (the latter obtained via public opinion polling in each state). Both the MSNBC article and the original scientific publication discuss how caution is warranted in interpreting the findings, both in terms of correlation and causality, and the ecological fallacy. Indeed, Barrowman writes that, "My goal here has not been to criticize the authors of this study, nor the media." Instead, his concern appears to be that the general public may draw improper conclusions from the study. All in all, however, I would say the scientific article -- and media and blog coverage thereof -- have done a public service by promoting an exchange of ideas about how the study's findings might reasonably be explained.

Saturday, July 18, 2009

I recently finished reading a new book by Johns Hopkins University sociologist Andrew Cherlin entitled The Marriage-Go-Round: The State of Marriage and the Family in America Today. As the title implies, the U.S. has a lot of couple and family turnover. Though Americans' high rates of marriage and divorce are well-known, there's a third element, of which I wasn't really familiar. Namely, Americans also have a high rate of re-partnering after the break-up of marital and non-marital couples. An illustrative statistic Cherlin cites is the percentage of women in different countries who have "three or more live-in partners (married or cohabiting) by age thirty-five" (p. 19). In the U.S., it's 10%, whereas in other English-speaking nations (those in Europe, as well as Canada, Australia, and New Zealand), none was higher than 4.5%.

Cherlin notes further that, "Children who experiences a series of transitions appear to have more difficulties than children raised in stable two-parent families and perhaps even more than children raised in stable lone-parent families" (p. 20). He acknowledges, however, that, "we cannot be sure that experiencing parents and partners moving in and out of the house actually causes the difficulties researchers have found in children. Some aspects of the parents' personalities or abilities could affect both the stability of their partnerships and their children's behavior" (pp. 20-21). The possibility that a genetic-based factor, present in the parent and passed to the children, could cause both the parent's relationship difficulties and the children's behavior problems is also acknowledged.

Cherlin discusses two research approaches that attempt to get around these interpretational difficulties. Regarding the genetic issue:

A way to test this possibility is to compare the adjustment of biological children, who share their parents' genes, with adopted children, who do not. If having genes in common is the root cause of the difficulties we see in families of divorce, we would expect that biological children of divorced parents would show more problems after a parental divorce than would adopted children. But that's not what researchers find... (p. 21).

In the endnotes (pp. 216-217), Cherlin adds the following:

Paula Fomby and I looked at this question another way. If what's happening is merely that parents are passing along traits that lead to difficulties, then, we reasoned, children who are acting out or delinquent should be more likely to have parents who acted out or were delinquent when they were children... We examined the records of a twenty-year national study that followed women beginning when they were teenagers. Most of the women became mothers during the study. We found that even after we took into account whether the mothers had, when they were teenagers, used drugs, shoplifted, stolen something, or had early sexual intercourse, their children still had more behavior problems and admitted to more delinquency if their mothers had had more partners. Our study suggests that experiencing a series of partnerships may be, at least in part, a true cause of children's difficulties.

These findings were said to hold for white families, but not for black families. With non-experimental research, alternative explanations for findings are virtually always present. The research described by Cherlin is noteworthy, in my mind, for the creative research designs used in an attempt to rule out some of the leading alternative interpretations.

Thursday, July 9, 2009

The following is a message from Judea Pearl to the SEMNET (Structural Equation Modeling) discussion list (conveyed by Dr. Pearl's colleague Stephen Sivo). Given Dr. Pearl's apparent intent to have these announcements publicized to a wide audience, I (Alan) have reprinted it below (lightly edited for apparent typos and ease of accessing links)...Dear Colleagues in Causality,

Below, a few items that I thought would be of interest to researchers active in causal reasoning.

1. A new article, authored by Ilya Shpitser and myself is now posted on the UCLA Causality-Blog (see also here). It offers a solution to the problem of evaluating "Effects of Treatment on the Treated (ETT)." The problem is of theoretical interest because ETT, despite its blatant counterfactual character (e.g., "I just took an aspirin, perhaps I shouldn't have?"), can be evaluated from experimental studies in many, though not all, cases. Characterizing those cases illuminates therefore the empirical content of counterfactuals.

2. Many of you have commented on my article "Myth, Confusion and Science in Causal Analysis" (inspired by Don Rubin), a revised version of which is now posted on our website here . I would like to encourage a blog-discussion on the main points raised there. For example:

2.1. Whether graphical methods are in some way "less principled" than other methods of analysis.2.2. Whether confounding bias can only decrease by conditioning on a new covariate.2.3 Whether the M-bias, when it occurs, is merely a mathematical curiosity, unworthy of researchers' attention.2.4. Whether Bayesianism instructs us to condition on all available measurements.

If you feel strongly about defending any of these claims (which seem to bestill simmering in certain circles, see video), the Causality-Blog can be an effective arena for airing them in an open discussion. Requests for anonymity will be honored.

3. Forbes magazine ran an issue on artificial intelligence last week, to which I contributed a popular article on progress in causal analysis (from my humble perspective, of course). Comments are welcome.

4. I have volunteered to give a tutorial at the JSM meeting (Washington, DC, August 5, 2009, 2-4 pm) on "Causal Analysis in Statistics: A Gentle Introduction." If any of your colleagues or students could benefit from such tutorial, I promise to be truly gentle.

5. Just before the tutorial, at 12 noon, there will be a book-signing gathering at the Cambridge University Press booth, where I will be signing copies of the 2nd Edition of Causality (and will engage in gossip and debates about where causality is heading).

Best wishes, and May clarity shine over causality land,Judea Pearl

Note that all of Dr. Pearl's requests for blog discussion pertain to his blog at UCLA. I have thus turned off the comments option here.

Monday, June 15, 2009

Today's New York Times has an article on the link between moderate alcohol consumption and lower heart disease, and whether health officials should actively recommend a daily drink or two for the public. At a correlational level, the alcohol-heart health relationship appears well established. As the piece in the Times delves into, the lack of true experimentation (in this case via Randomized Clinical Trials) gives skeptics something to hang their hats on. The following are some key excerpts of the article:

For some scientists, the question will not go away. No study, these critics say, has ever proved a causal relationship between moderate drinking and lower risk of death — only that the two often go together. It may be that moderate drinking is just something healthy people tend to do, not something that makes people healthy.

“The moderate drinkers tend to do everything right — they exercise, they don’t smoke, they eat right and they drink moderately,” said Kaye Middleton Fillmore, a retired sociologist from the University of California, San Francisco, who has criticized the research. “It’s very hard to disentangle all of that, and that’s a real problem.” ...

“The bottom line is there has not been a single study done on moderate alcohol consumption and mortality outcomes that is a ‘gold standard’ kind of study — the kind of randomized controlled clinical trial that we would be required to have in order to approve a new pharmaceutical agent in this country,” said Dr. Tim Naimi, an epidemiologist with the Centers for Disease Control and Prevention.

The article goes on to discuss how clinical trials might be designed, but also their potential ethical and logistical difficulties.

I've just read The Numbers Game and, for purposes of the present blog, Chapter 12 on "Causation" is most relevant. The book's chapters are generally around 10-20 pages each, with the Causation chapter toward the shorter end. Much of this chapter presents standard material, such as a set of correlational scenarios that might tempt a reader to draw causal conclusions but ultimately turn out to be more plausibly explained by third variables. Beyond this, however, I feel the authors provide some useful insights:

What seems often to determine how easily we spot causation/correlation errors is how fast a better explanation comes to mind: thinking of decent alternatives slows conclusions and sows skepticism (p. 186).

AND

Restlessness for the true cause is a constructive habit, an insurance against gullibility. And though correlation does not prove causation, it is often a good hint, but a hint to start asking questions, not to settle for easy answers (191-192)

[As somewhat of an aside, the first of the two above statements bears some similarity in my mind to the late causal-attribution theorist Hal Kelley's concept of discounting.]

I would urge teachers of undergraduate research methods to consider using The Numbers Game (or specific chapters therein) to supplement their main textbooks. The writing is lively and the examples should help students grasp key concepts.